應用資料探勘技術探討奢華餐廳顧客之服務體驗與推薦對滿意度之影響──以臺灣米其林餐廳為例

Using data mining techniques to explore the impact of service experience and recommendation on customer satisfaction in luxury restaurants: A case study of Michelin restaurants in Taiwan

利用線上評論資料瞭解顧客需求，日益受到學者與業者的重視。因此，本研究運用「資料探勘」技術，以米其林餐廳作為研究對象，蒐集了TripAdvisor網站上的四種服務體驗（食物、服務、實惠、氛圍）、顧客滿意度及顧客推薦等資料，用以瞭解四種服務體驗對顧客滿意度的影響及顧客推薦對此兩者關係的調節作用。研究結果顯示，四種服務體驗對顧客滿意度有正向顯著的影響，而顧客推薦也對兩者間的關係產生了調節作用。研究結果可提供奢華餐廳改進經營和服務品質之參考。

The use of online review data to understand customer needs has been increasingly emphasized by academics and industry players. Therefore, this study used the“data mining”technique to collect data on the four types of service experiences (food, service, value, and atmosphere), customer satisfaction, and customer recommendations on the TripAdvisor website using Michelin restaurants as the research target, in order to understand the effect of the four types of service experiences on customer satisfaction and the moderating effect of customer recommendations on the relationship between the two. The results of the study showed that the four types of service experience had a positive and significant effect on customer satisfaction, and customer recommendation moderated the relationship between the two. The results of this study can be used as a reference to improve the operation and service quality of luxury restaurants.